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对COVID-19临床和实验室数据的回顾性分析:在不同的并发症中构建一个多变量模型

Mahdieh Shokrollahi Barough¹, Mohammad Darzi², Masoud Yunesian³

¹Department of Immunology, School of Medicine Iran University of Medical Sciences, Tehran, Iran; Immunology research center institute of immunology and infectious diseases Iran University of Medical Sciences, Tehran, Iran; ATMP Department, Breast Cancer Research Center, Motamed Cancer Institute, ACECR, Tehran, Iran.

Journal of infection and public health

|October 25, 2024

概括

在男性中,COVID-19的死亡率更高,并且在55岁以上的人群中预测的死亡率更高. 病是最致命的并发症,而CT扫描对死亡没有预测价值.

科学领域:

医学研究医学研究
流行病学流行病学
公共卫生公共卫生

背景情况:

了解COVID-19病原体需要对疾病机制进行同质研究.
确定临床和实验室预测因素对于预后和治疗至关重要.
这项研究旨在使用并发症和实验室指标预测COVID-19死亡率.

研究的目的:

分析并发症和实验室参数,以预测COVID-19死亡率.
在同质的患者队列中确定死亡率的关键预测因素.
为制定有效的治疗策略和改善患者预后提供信息.

主要方法:

对7500名COVID-19患者 (2022-2022) 的回顾性队列研究.
收集和分析临床,实验室和并发病数据.
使用机器学习进行特征识别和预测评分.

主要成果:

男性COVID-19患者的死亡率比女性 (17%) 高 (19.3%).
癌症和阿尔茨海默病是与长期住院相关的常见并发症.
病 (KD) 是最致命的并发病 (45%的死亡率);55岁以上是最强的死亡率预测因素.
WBC,Cr,CRP,ALP和VBG-HCO3是共患病的显著预测因素;CT扫描得分没有预测.

结论:

年龄是COVID-19预后的一个关键因素,特别是对于老年患者.
病显著影响COVID-19死亡率结果.
结合并发症和实验室数据的预测模型可以指导临床管理.

关键词:

在 COVID-19 疫情中,伴随性疾病伴随性疾病功能选择功能选择实验室数据实验室数据机器学习是机器学习.

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